code: def setup_args(parser=None):
      if parser is None:
          parser = ParlaiParser(True, True, "Evaluate a model")
      # Get command line arguments
      parser.add_argument(
          "-rf",
          "--report-filename",
          type=str,
          default="",
          help="Saves a json file of the evaluation report either as an "
          'extension to the model-file (if begins with a ".") or a whole '
          "file path. Set to the empty string to not save at all.",
      )
      parser.add_argument(
          "--world-logs",
          type=str,
          default="",
          help="Saves a jsonl file of the world logs."
          "Set to the empty string to not save at all.",
      )
      parser.add_argument(
          "--save-format",
          type=str,
          default="conversations",
          choices=["conversations", "parlai"],
      )
      parser.add_argument(
          "--area-under-curve-digits",
          "-auc",
          type=int,
          default=-1,
          help="a positive number indicates to calculate the area under the "
          "roc curve and it also determines how many decimal digits of the "
          "predictions to keep (higher numbers->more precise); also used "
          "to determine whether or not to calculate the AUC metric",
      )
      parser.add_argument(
          "--area-under-curve-class",
          "-auclass",
          type=str,
          default=None,
          nargs="*",
          help="the name(s) of the class to calculate the auc for",
      )
      parser.add_argument("-ne", "--num-examples", type=int, default=-1)
      parser.add_argument(
          "-d", "--display-examples", type="bool", default=False
      )
      parser.add_argument(
          "-ltim", "--log-every-n-secs", type=float, default=10
      )
      parser.add_argument(
          "-mcs",
          "--metrics",
          type=str,
          default="default",
          help="list of metrics to show/compute, e.g. all, default,"
          "or give a list split by , like "
          "ppl,f1,accuracy,hits@1,rouge,bleu"
          "the rouge metrics will be computed as rouge-1, rouge-2 and rouge-l",
      )
      parser.add_argument(
          "-micro",
          "--aggregate-micro",
          type="bool",
          default=False,
          help="Report micro-averaged metrics instead of macro averaged metrics.",
          recommended=False,
      )
      WorldLogger.add_cmdline_args(parser, partial_opt=None)
      TensorboardLogger.add_cmdline_args(parser, partial_opt=None)
      parser.set_params(datatype="valid")
      return parser
  
imports: from parlai.core.params import ParlaiParser, print_announcements
  from parlai.core.agents import create_agent
  from parlai.core.logs import TensorboardLogger
  from parlai.core.metrics import aggregate_named_reports, aggregate_unnamed_reports, Metric
  from parlai.core.opt import Opt
  from parlai.core.worlds import create_task
  from parlai.utils.misc import TimeLogger, nice_report
  from parlai.utils.world_logging import WorldLogger
  from parlai.core.script import ParlaiScript, register_script
  from parlai.utils.io import PathManager
  import parlai.utils.logging
  import json
  import os
  import random
  from parlai.utils.distributed import is_primary_worker, all_gather_list, is_distributed, get_rank
label_desc: Use image node_id 1 for calling a global function with example usage: setup_args(parser) and returns: parser